Generalized Information Matrix Tests (GIMTs) have recently been used for detecting the presence of misspecification in regression models in both randomized controlled trials and observational studies. In this paper, a unified GIMT framework is developed for the purpose of identifying,...

This note demonstrates that in applied regression analysis, the variance of a coefficient of interest may decrease from the inclusion of a control variable, contrasting with Clarke's assertion (2005, 2009) that the variance can only increase or stay the same. Practitioners may thus be...

The objective of this research is to introduce in literature new measures of accuracy for point forecasts (radical of order n of the mean of squared errors, mean for the difference between each predicted value and the mean of the effective values, ratio of radicals of sum of squared errors...

The replicability and credibility crisis in psychology and economics sparked the debate on underpowered experiments, publication biases, and p-hacking. Analyzing the number of independent observations of experiments published in Experimental Economics, Games and Economic Behavior, and the...

This study addresses the issue of the presence of a unit root on the growth rate estimation by the least-squares approach. We argue that when the log of a variable contains a unit root, i.e., it is not stationary then the growth rate estimate from the log-linear trend model is not a valid...

This note demonstrates that in applied regression analysis, the variance of a coefficient of interest may decrease from the inclusion of a control variable, contrasting with Clarke's assertion (2005, 2009) that the variance can only increase or stay the same. Practitioners may thus be...

In the physical sciences, order and disorder refer to the presence or absence of some symmetry or correlation in a many-particle system. It follows that it is important to examine whether there is any regularity hidden in the phase transition of the disorder-order relationship. In this paper a...

The paper proposes a new algorithm for finding the confidence set of a collection of forecasts or prediction models. Existing numerical implementations for finding the confidence set use an elimination approach where one starts with the full collection of models and successively eliminates the...

The objective of this research is to introduce in literature new measures of accuracy for point forecasts (radical of order n of the mean of squared errors, mean for the difference between each predicted value and the mean of the effective values, ratio of radicals of sum of squared errors...

Inference using large datasets is not nearly as straightforward as conventional econometric theory suggests when the disturbances are clustered, even with very small intra-cluster correlations. The information contained in such a dataset grows much more slowly with the sample size than it would...